Anthropic has closed a USD 65 billion Series H funding round at a post-money valuation of USD 965 billion, in what may be its final private raise before an IPO.
The round was co-led by Altimeter Capital, Dragoneer, Greenoaks, Sequoia Capital, Capital Group, Coatue, and D1 Capital Partners, among others. Institutional participants included Baillie Gifford, Blackstone, Brookfield, D.E. Shaw Ventures, DST Global, and Fidelity Management & Research. Strategic infrastructure partners Samsung, SK Hynix, and Micron also joined the round.
Of the total raised, USD 15 billion represents previously committed investments from hyperscalers, including a USD 5 billion contribution from Amazon.
Use of funds and product context
Anthropic has stated that proceeds will be directed towards safety and interpretability research, expanding compute capacity to meet demand for its Claude models, and scaling its product and partnership operations.
The funding announcement coincided with the release of Claude Opus 4.8, a new model positioned for agentic tasks and advanced coding, with a stated emphasis on honesty and self-correction. Separately, Anthropic is reportedly considering a broader rollout of models comparable to Mythos, its cybersecurity-focused model that has so far been released in limited form due to safety considerations.
The company's run rate revenue crossed USD 47 billion earlier in May 2026, driven in part by enterprise adoption of Claude Code. Anthropic has also indicated it expects revenue to grow 130% year-on-year, which would bring it to its first operating profit.
Competitive landscape ahead of IPO
The raise positions Anthropic competitively as it approaches a potential public listing. OpenAI completed a USD 122 billion funding round in March 2026 at a post-money valuation of USD 852 billion. SpaceX, which merged with xAI earlier in 2026, is targeting a valuation of USD 2 trillion in its pending IPO and is reported to be seeking more than USD 75 billion in that process.
The scale of recent fundraising across AI companies reflects sustained institutional appetite for large-language-model infrastructure and application platforms, particularly as enterprise demand for AI-assisted development tooling continues to grow.
